In this section, your instructor discusses Casting.<br/<br/>>

This clip is from the chapter "Errors and Data Types" of the series "C++ for Beginners".Outputting Errors

In this lesson, your instructor discusses variables.<br/<br/>>

This clip is from the chapter "Variables and Assignments" of the series "C++ for Beginners".Variables and identifiers

We will first train the CNN model based on the dataset from Kaggle and then we will test that model to test a human face to predict one of the emotions. In this video, we show how to develop a CNN for emotion prediction from facial...

This video explains the library.<br/<br/>>

This clip is from the chapter "Functions" of the series "The Complete C++ Developer Course".This section discusses the various functions in C++.

A demonstration of how "if statements" are used in programming.

We will look at two examples for developing a more robust recommendation systems using FM. We will also see FM and their applications in the cold-start recommendation problem. • Understand the factorization machines • Look at the cold...

In this video, we will tune the CNN hyperparameters. • Tune the CNN hyperparameters

CNNs are a type of feedforward neural network in which the connectivity pattern between its neurons is based on the animal visual cortex. We will also see CNN architecture and convolution operations. • Look at CNNs and drawbacks of...

An introduction to using arrays in programming.

In this lesson, your instructor discusses string classes.<br/<br/>>

This clip is from the chapter "STL Strings" of the series "C++ for Beginners".Creating a String

Nothing feels worse than getting a new Arduino board and then managing to destroy it after a manner of minutes.



This week's episode builds on the previous episode by highlighting five more ways you...

In this video, we will use python to write a simple ensemble learning model for classification. • We will use Jupyter Notebook to execute our code • Use Iris dataset to perform classification • Use hard voting and soft voting for...

A description of a code library in Arduino programming.

In this section, your instructor examines the comparison operator types and the logical operator types.
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This clip is from the chapter "Operators and Precedence" of the series "C++ for Beginners".Understanding Comments:...

In this lesson, your instructor discusses how to process data by using the Bubble Sort.<br/<br/>>

This clip is from the chapter "Input, Process and Output" of the series "C++ for Beginners".null

The TensorFlow programming model signifies how to structure your predictive models. • Look at the steps for structuring the model

Want to do multiple thing with Arduino? Then master the Arduino millis function!

Hello, I hope you’re doing fantastic. In this series, we’ve been talking about using the Arduino millis function to create...

A walk through of a User Defined Function in programming.

In this lesson, David examines several types of operators and how to use them.<br/<br/>>

This clip is from the chapter "Operators and Precedence" of the series "C++ for Beginners".Understanding Comments: Useful VS Redundant

Your instructor, David, demonstrates Cin stream, which allows simple keyboard input.<br/<br/>>

This clip is from the chapter "Errors and Data Types" of the series "C++ for Beginners".Outputting Errors

Your instructor, David, discusses the Character Data Type.<br/<br/>>

This clip is from the chapter "Variables and Assignments" of the series "C++ for Beginners".Variables and identifiers

The listener is new to algorithms and does not know about the sampling algorithms.

• Introduce the listener to the std::sample algo
rithm
• Show how it works and explain the different versions
available
• Reinforce...

In this video, we’ll see the best practices that we can use to create effective dashboards. • Best practices for creating effective dashboards • Implement best practices for effective dashboards

We will see how we can improve the previous predictive model with minimum effort using TF-IDF. • Use Word2vec for doing sentiment analysis